Terra and Aqua: new data for epidemiology and public health

This article writed by J.Tatem was published in International Journal of Applied Earth Observation and Geoinformation 6 (2004)

Extract of International Journal of Applied Earth Observation and Geoinformation 6 (2004)

Andrew J. Tatem [1], Scott J. Goetz [2] , Simon I. Hay (1) and [3]

Abstract Earth-observing satellites have only recently been exploited for the measurement of environmental variables of relevance to epidemiology and public health. Such work has relied on sensors with spatial, spectral and geometric constraints that have allowed large-area questions associated with the epidemiology of vector-borne diseases to be addressed. Moving from pretty maps to pragmatic control tools requires a suite of satellite-derived environmental data of higher fidelity, spatial resolution, spectral depth and at similar temporal resolutions to existing meteorological satellites. Information derived from sensors onboard the next generation of moderate-resolution Earth-observing sensors may provide the key. The MODIS and ASTER sensors onboard the Terra and Aqua platforms provide substantial improvements in spatial resolution, number of spectral channels, choices of bandwidths, radiometric calibration and a much-enhanced set of pre-processed and freely available products. These sensors provide an important advance in moderate-resolution remote sensing and the data available to those concerned with improving public health.


For the past 30 years, the sensors on Earth- observing satellites have provided an unprecedented view of the land surface, but have only more recently been exploited for the measurement of environmental variables of relevance to epidemiology and public health (Hay, 1997, 2000; Hay et al., 1997; Kazmi and Usery, 2000; Thomson and Connor, 2000). A wide- variety of vector-borne diseases have been investi- gated (Randolph, 2000; Rogers et al., 2002a; Tatem et al., 2003) but predominant among the interests of the authors have been the application of remotely sensed data to describing spatial distribution and temporal dynamics of malaria epidemiology in sub-Saharan Africa (Hay et al., 2000a; Omumbo et al., 2002). There are between 300 and 500 million clinical cases of the mosquito-borne disease malaria every year, resulting in 1–3 million deaths, of which over 90% occur in sub-Saharan Africa (Greenwood and Muta- bingwa, 2002; Sachs and Malaney, 2002). Every 40 s a child dies of malaria, rendering it one of the top global killers and a massive barrier to development in Africa. Sadly, despite years of progress fighting the disease, drug and insecticide resistance, underfunding, along with environmental, climatic and population changes, have meant that mortality from malaria is now increasing once again in sub-Saharan Africa. Empirical malariometric data in combination with environmental information from Earth-observing satellites have now been used to map mosquito vector distributions, the force of infection as measured by annual entomological inoculation rates, disease pre- valence using parasite rate surveys and malaria seasonality (for a review, see Hay et al., 1998; Rogers et al., 2002b). The justifications for such maps (Snow et al., 1996) include (a) informing the appropriate choice of malaria control, since different control options are optimal in different endemic settings; (b) an evidence-base to planning the magnitude of control operations by determining population at risk; © defining optimal and equitable spatial targeting of interventions; (d) determining optimal timing of control, for example, when in the year to impregnate bed-nets with insecticide and (e) assisting in the assessment of control interventions by documenting reduction in malaria with respect to pre-intervention levels. These efforts have been achieved at continental and regional scales and at higher spatial resolutions for specific sub-regional and county level areas of interest. While this initial round of work has been valuable in establishing methodological approaches and a macro-level understanding of malaria distribution and burden, it has become more obvious that to fully utilize such information for an increased evidence- base for malaria planning and control, several limitations need to be addressed. Among these are the need to define more accurately human population distribution and the effects urbanization, water body distribution and land use have on these often spatially- coarse malaria transmission, prevalence and morbidity estimates. The higher spatial resolution of disease information needs to be combined in decision-support systems that require much more detailed information on health facility and service delivery infrastructure than is currently available. The high temporal, spatial and spectral resolution of sensors onboard NASAs Terra and Aqua satellites offer a significant opportu- nity in providing the data to help address some of these limitations. It is these data and their potential utility for future public health studies that are the focus of the current review. Not only does this review aim to distil salient information from a diverse and usually unfamiliar literature to those concerned with both public health and remote sensing, but also to highlight the important considerations with reference to use of these data in epidemiological and public health applications.


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[1TALA Research Group, Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK

[2he Woods Hole Research Center, P.O. Box 296, Woods Hole, Massachusetts, MA 02543-0296, USA

[3Kenya Medical Research Institute/Wellcome Trust Collaborative Programme, P.O. Box 43640, 00100 Nairobi GPO, Kenya

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